Robust Image Security Throught Hill Cipher Advancements using Machine Learning
Robust Image Security Throught Hill Cipher Advancements using Machine Learning
G.Manoj Kumar 1, Maradana Raju 2
1 Assistant Professor & Training & Placement Officer, 2 MCA Final Semester,
Master of Computer Applications, Sanketika Vidya Parishad Engineering College, Vishakhapatnam, Andhra Pradesh, India
Manoj kumar.mca@svpec.edu.in,maradanaraju95735@gmail.com
ABSTRACT
In today's digital era, ensuring the security of sensitive information, especially in image data, is of paramount importance. The security of digital images is becoming increasingly critical due to the widespread transmission of images across networks, making them vulnerable to unauthorized access, tampering, and data breaches. Therefore, encryption is essential to safeguard the confidentiality and integrity of digital images. The Advanced Hill Cipher Algorithm presents a significant stride toward achieving robust image data encryption in the face of evolving cybersecurity challenges by enhancing the traditional Hill Cipher with improved key generation techniques and resistance to common cryptographic attacks. By leveraging matrix-based transformations and incorporating higher-dimensional keys, the algorithm ensures stronger diffusion and confusion properties, making it more secure against brute-force and known-plaintext attacks. Additionally, it can be adapted for color images by encrypting pixel values across multiple channels, thereby maintaining visual distortion and preventing information leakage. Its computational efficiency also makes it suitable for real-time applications such as secure image sharing, medical imaging, and military communications. Overall, the Advanced Hill Cipher Algorithm offers a reliable and scalable approach to protecting digital image data while balancing security and performance requirements.